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RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
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In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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From FreEM to D'AlemBERT ; From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French
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In: Proceedings of the 13th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-03596653 ; Proceedings of the 13th Language Resources and Evaluation Conference, European Language Resources Association, Jun 2022, Marseille, France (2022)
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Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
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In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
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Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost
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In: ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03613101 ; ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, May 2022, Dublin, Ireland (2022)
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Imputing out-of-vocabulary embeddings with LOVE makes language models robust with little cost
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In: ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03613101 ; ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, May 2022, Dublin, Ireland (2022)
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Structured, flexible, and robust: comparing linguistic plans and explanations generated by humans and large language models ...
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On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages ...
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Chen, Fuxiang. - : Federated Research Data Repository / dépôt fédéré de données de recherche, 2022
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Sentence Level Embedding Detoxification via Toxic Component Removal ...
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: University of Virginia, 2022
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| 9 |
MIss RoBERTa WiLDe: Metaphor Identification Using Masked Language Model with Wiktionary Lexical Definitions
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In: Applied Sciences; Volume 12; Issue 4; Pages: 2081 (2022)
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| 10 |
Considering Commonsense in Solving QA: Reading Comprehension with Semantic Search and Continual Learning
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4099 (2022)
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| 11 |
Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models
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In: Applied Sciences; Volume 12; Issue 1; Pages: 491 (2022)
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| 12 |
Commonsense Knowledge-Aware Prompt Tuning for Few-Shot NOTA Relation Classification
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In: Applied Sciences; Volume 12; Issue 4; Pages: 2185 (2022)
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| 13 |
Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages
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In: Future Internet; Volume 14; Issue 3; Pages: 69 (2022)
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| 14 |
Correcting Diacritics and Typos with a ByT5 Transformer Model
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2636 (2022)
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| 15 |
Language Competition and Language Shift in Friuli-Venezia Giulia: Projection and Trajectory for the Number of Friulian Speakers to 2050
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In: Sustainability; Volume 14; Issue 6; Pages: 3319 (2022)
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Abstract:
This article analyses how the number of speakers of the Friulian language changes over time in the territory where this language is traditionally spoken, that is, the provinces of Udine, Pordenone, and Gorizia, located in the north-east of Italy in the autonomous region of Friuli-Venezia Giulia. The aim of this research is twofold. First, it illustrates how the number of speakers of Friulian evolved over the past 40 years. To this end, we provide an overview of the findings of empirical studies on the Friulian language from 1977, 1998, and 2014. We complement these findings with population figures, birth and death rates, as well as data on migration and language transmission in order to provide a better understanding of the current situation in the three provinces. Second, these data are used to set up a mathematical language dynamic (or language competition) model. With the help of this empirically informed model, we derive projections for the future of the Friulian language in the three provinces. The results show that the number of Friulian speakers will decrease from 600,000 in 2014 to about 530,000 in 2050 (−11%), and that the number of regular Friulian speakers will decreases from 420,000 to 320,000 (−23%). By 2050, about 30% of the population will speak Friulian regularly and about 50% will speak Friulian regularly or occasionally. Only in the province of Udine will Friulian speakers still be in a clear majority. The analysis suggests that a stronger commitment to language policy protecting and promoting Friulian is needed in order to counteract these trends.
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Keyword:
Friulian language; language competition models; language policy; minority language
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URL: https://doi.org/10.3390/su14063319
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An Information Theoretic Approach to Symbolic Learning in Synthetic Languages
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In: Entropy; Volume 24; Issue 2; Pages: 259 (2022)
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Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition
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In: Machine Learning and Knowledge Extraction; Volume 4; Issue 1; Pages: 254-275 (2022)
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Language and vision in conceptual processing: Multilevel analysis and statistical power ...
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Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics.
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